What are SLOs, SLAs, and SLIs? A complete guide to service reliability metrics

Key statistics and quick answers

Quick definitions:

SLI (Service Level Indicator): The actual measurement (e.g., "99.95% uptime last month")
SLO (Service Level Objective): The internal target (e.g., "99.9% uptime goal")
SLA (Service Level Agreement): The contractual promise with consequences (e.g., "99.9% uptime or 10% credit")

Industry benchmarks (2024 data):

Service Type	Typical SLA	Industry Leader SLA	Cost of Downtime/Hour
E-commerce Platform	99.9%	99.99% (Amazon)	$500,000 – $1,100,000
SaaS B2B	99.5%	99.95% (Salesforce)	$100,000 – $540,000
Financial Services	99.95%	99.999% (Visa)	$1,000,000 – $5,000,000
Social Media	99.9%	99.95% (LinkedIn)	$200,000 – $450,000

Key facts:

73% of organizations experienced an outage costing over $100,000 in the last year
Average SLA breach penalty: 5-25% service credit
Most common SLO target: 99.9% uptime (allows 43.8 minutes downtime/month)
Error budget calculation: (100% - SLO%) × time period
ROI of SRE practices: 3-5x reduction in incident costs within 12 months

What is an SLI (Service Level Indicator)?

Definition and purpose

An SLI answers the question: "How are we actually performing right now?"

Service Level Indicators are the raw, quantitative measurements that tell you exactly how your service is performing. Think of them as the speedometer in your car - they show the actual speed, not the speed limit or your desired speed.

The 5 golden SLI categories

Availability SLIs
- Measurement: Percentage of successful requests / total requests
- Example: "99.95% of health check requests succeeded in the last 30 days"
- Real-world case: Netflix measures availability as successful stream starts divided by total attempts
Latency SLIs
- Measurement: Response time at specific percentiles (p50, p95, p99)
- Example: "95% of API requests completed in under 200ms"
- Real-world case: Google Search aims for p99 latency under 1000ms globally
Throughput SLIs
- Measurement: Requests processed per second/minute
- Example: "Payment system processed 10,000 transactions per minute"
- Real-world case: Stripe processes 250+ million API requests daily (2,900/second average)
Error rate SLIs
- Measurement: Failed requests / total requests
- Example: "0.01% error rate on database queries"
- Real-world case: Amazon DynamoDB maintains <0.001% error rates on standard operations
Durability SLIs
- Measurement: Percentage of data retained without corruption
- Example: "99.999999999% (11 nines) data durability"
- Real-world case: Amazon S3 guarantees 11 nines of durability for objects

How to calculate SLIs: Step-by-step

Step 1: Choose your measurement window

Real-time: Last 5 minutes
Short-term: Last 24 hours
Monthly: Rolling 30 days
Quarterly: Rolling 90 days

Step 2: Collect raw data

{ "total_requests": 1000000, "successful_requests": 999500, "failed_requests": 500, "measurement_period": "30 days" }

Step 3: Apply the formula

Availability SLI = (successful_requests / total_requests) × 100
Example: (999,500 / 1,000,000) × 100 = 99.95%

Step 4: Track trends

Daily averages
Weekly patterns
Monthly comparisons
Quarterly reports

What is an SLO (Service Level Objective)?

Definition and strategic importance

An SLO answers the question: "What level of service do we want to provide?"

Service Level Objectives are your internal targets that balance reliability with innovation velocity. They define the minimum acceptable performance before your team needs to take action.

The 7-step SLO setting process

Understand user expectations
- Survey data: "Users expect <2 second page loads"
- Industry benchmarks: "Competitors offer 99.9% uptime"
- Historical performance: "We achieved 99.95% last quarter"
Define critical user journeys (CUJs)
- Login and authentication
- Core feature usage
- Payment processing
- Data export/import
Set realistic targets

Availability Target	Monthly Downtime	Annual Downtime	Use Case
99%	7.2 hours	3.65 days	Development environments
99.9%	43.8 minutes	8.76 hours	Standard web applications
99.95%	21.9 minutes	4.38 hours	Business-critical SaaS
99.99%	4.38 minutes	52.56 minutes	High-availability services
99.999%	26.3 seconds	5.26 minutes	Mission-critical systems

Calculate error budgets
- Formula: Error Budget = (100% - SLO%) × Time Period
- Example: 99.9% SLO = 0.1% error budget = 43.8 minutes/month
Create alerting thresholds
- 50% budget consumed: Engineering awareness
- 75% budget consumed: Incident response team engaged
- 90% budget consumed: Feature freeze consideration
- 100% budget consumed: All-hands response
Document decision framework

IF error_budget_remaining < 25% THEN
  - Freeze non-critical deployments
  - Focus on reliability improvements
  - Increase monitoring coverage

Review and adjust quarterly
- Too easy to meet? Increase target
- Consistently missed? Lower target or invest in reliability

Real-world SLO examples from tech leaders

1. Google Cloud Platform

Service: Cloud Storage
SLO: 99.95% availability for multi-region
Error budget: 21.9 minutes/month
Consequence: If breached, 10-50% credit depending on severity

2. Spotify

Service: Music streaming
SLO: 99.9% successful stream starts
Error budget: 43.8 minutes/month
Innovation trade-off: Allows rapid feature deployment

3. Uber

Service: Ride matching
SLO: 99.99% availability for ride requests
Error budget: 4.38 minutes/month
Critical because: Direct revenue impact per minute of downtime

4. GitHub

Service: Git operations
SLO: 99.95% success rate for git push/pull
Error budget: 21.9 minutes/month
Measurement: Excluding planned maintenance windows

What is an SLA (Service Level Agreement)?

Definition and legal framework

An SLA answers the question: "What did we promise our customers, and what happens if we fail?"

Service Level Agreements are legally binding contracts that define the minimum service levels a provider must deliver and the remedies or penalties if they fail to meet them.

The 10 essential components of an SLA

Service description
- Exact services covered
- Service boundaries
- Included vs. excluded features
Availability commitments

Monthly Uptime Percentage: 99.9%
Calculation: (Total Minutes - Downtime Minutes) / Total Minutes × 100
Measurement Period: Calendar month

Performance metrics
- Response time: "95% of requests under 500ms"
- Throughput: "Support 10,000 concurrent users"
- Error rate: "Less than 0.1% failed requests"
Support commitments

Severity	Initial Response	Resolution Target	Escalation
Critical (P1)	15 minutes	4 hours	VP Engineering
High (P2)	1 hour	24 hours	Engineering Manager
Medium (P3)	4 hours	72 hours	Team Lead
Low (P4)	24 hours	Best effort	Support Team

Credit structure

| Monthly Uptime | Service Credit | | --- | --- | | 99.9% - 100% | 0% | | 99.0% - 99.9% | 10% | | 95.0% - 99.0% | 25% | | Below 95.0% | 50% |

Exclusions
- Planned maintenance windows
- Force majeure events
- Customer-caused issues
- Third-party service failures
Reporting requirements
- Monthly availability reports
- Incident post-mortems for breaches
- Quarterly business reviews
Measurement methodology
- Monitoring locations
- Sampling frequency
- Calculation formulas
- Dispute resolution process
Notification procedures
- Incident communication SLA
- Status page updates
- Email notifications
- Executive escalation paths
Termination clauses
- Chronic breach conditions
- Refund policies
- Data portability guarantees
- Transition assistance

Industry-specific SLA examples

1. AWS (Amazon Web Services)

Service: EC2
SLA: 99.99% for instances in multiple AZs
Credits: 10% for <99.99%, 30% for <99.0%
Unique clause: Excludes individual instance failures

2. Microsoft Azure

Service: Virtual Machines
SLA: 99.95% for single VM, 99.99% for availability sets
Credits: 10% for <99.95%, 25% for <99%, 100% for <95%
Measurement: 5-minute intervals

3. Salesforce

Service: Sales Cloud
SLA: 99.9% availability
Credits: Days of service added to subscription
Reporting: Monthly uptime reports published publicly

4. Slack

Service: Business messaging
SLA: 99.99% for Enterprise Grid
Credits: 10× the duration of downtime
Innovation: Separate SLAs for different service tiers

Quick reference: SLI vs SLO vs SLA comparison table

What's the difference between SLI, SLO, and SLA?

Aspect	SLI (Service Level Indicator)
Definition	The actual, real-time measurement of your service performance. It's the raw data that tells you exactly how your system is performing right now.
Metrics examples	Availability: 99.97% uptime measured over last 30 days Latency: P95 response time = 187ms Error rate: 0.03% failed requests Throughput: 52,341 requests/second Durability: 99.999999999% data integrity
Use cases	Real-time monitoring: Dashboard showing current system health Incident detection: Alert when availability drops below 99.95% Performance tracking: Weekly performance reports Capacity planning: Identify when to scale infrastructure Root cause analysis: Correlate metrics during incidents
Audience	Engineering teams, SRE, DevOps
Frequency of change	Continuous (real-time data)
Consequences of missing	Alerts fired, incidents declared